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Quantum information processing offers promising advances for a wide range of fields and applications, provided that we can efficiently assess the performance of the control applied in candidate systems. That is, we must be able to determine…

Quantum Physics · Physics 2015-01-26 Christopher Granade , Christopher Ferrie , D. G. Cory

Quantum superposition, a cornerstone of quantum mechanics, enables systems to exist in multiple states simultaneously, giving rise to probabilistic outcomes. In quantum information science, conditional entropy has become a key metric for…

General Physics · Physics 2024-10-21 Daegene Song

Competitive on-line prediction (also known as universal prediction of individual sequences) is a strand of learning theory avoiding making any stochastic assumptions about the way the observations are generated. The predictor's goal is to…

Machine Learning · Computer Science 2007-05-23 Vladimir Vovk

In this work, we aim at augmenting the decisions output by quantum models with "error bars" that provide finite-sample coverage guarantees. Quantum models implement implicit probabilistic predictors that produce multiple random decisions…

Quantum Physics · Physics 2023-10-24 Sangwoo Park , Osvaldo Simeone

Common approaches to concurrent programming begin with languages whose semantics are naturally sequential and add new constructs that provide limited access to concurrency, as exemplified by futures. This approach has been quite successful,…

Programming Languages · Computer Science 2023-06-22 Klaas Pruiksma , Frank Pfenning

Conformal prediction is a framework for uncertainty quantification that constructs prediction sets for previously unseen data, guaranteeing coverage of the true label with a specified probability. However, the efficiency of these prediction…

Machine Learning · Computer Science 2026-01-06 Erfan Hajihashemi , Yanning Shen

Building on the standard theory of process algebra with priorities, we identify a new scheduling mechanism, called "constructive reduction" which is designed to capture the essence of synchronous programming. The distinctive property of…

Programming Languages · Computer Science 2025-08-07 Luigi Liquori , Michael Mendler

We consider the first-order theory of random variables with the probabilistic independence relation, which concerns statements consisting of random variables, the probabilistic independence symbol, logical operators, and existential and…

Information Theory · Computer Science 2021-08-18 Cheuk Ting Li

Quantified formulas pose a significant challenge for Satisfiability Modulo Theories (SMT) solvers due to their inherent undecidability. Existing instantiation techniques, such as e-matching, syntax-guided, model-based, conflict-based, and…

Artificial Intelligence · Computer Science 2025-08-20 Jan Jakubův , Mikoláš Janota

The context of this work is cooperative scheduling, a concurrency paradigm, where task execution is not arbitrarily preempted. Instead, language constructs exist that let a task voluntarily yield the right to execute to another task. The…

Programming Languages · Computer Science 2023-12-29 Reiner Hähnle , Ludovic Henrio

We present a new system S for handling uncertainty in a quantified modal logic (first-order modal logic). The system is based on both probability theory and proof theory. The system is derived from Chisholm's epistemology. We concretize…

Artificial Intelligence · Computer Science 2018-05-29 Naveen Sundar Govindarajulu , Selmer Bringsjord

The study of conditional $q$-entropies in composite quantum systems has recently been the focus of considerable interest, particularly in connection with the problem of separability. The $q$-entropies depend on the density matrix $\rho$…

Quantum Physics · Physics 2009-11-10 J. Batle , A. R. Plastino , M. Casas , A. Plastino

Applications in machine learning, optimization, and control require the sequential selection of a few system elements, such as sensors, data, or actuators, to optimize the system performance across multiple time steps. However, in…

Machine Learning · Statistics 2020-12-17 Vasileios Tzoumas , Ali Jadbabaie , George J. Pappas

Quantum measurement is a physical process. What physical resources and constraints does quantum mechanics require for measurement to produce the classical world we observe? Treating measurement as a fully unitary quantum process, our goal…

Quantum Physics · Physics 2025-12-09 Vishal Johnson , Ashmeet Singh , Reimar Leike , Philipp Frank , Torsten Enßlin

The growing study of time series, especially those related to nonlinear systems, has challenged the methodologies to characterize and classify dynamical structures of a signal. Here we conceive a new diagnostic tool for time series based on…

Other Statistics · Statistics 2017-07-05 G. Corso , T. L. Prado , G. Z. dos S. Lima , S. R. Lopes

The recently introduced framework of Graded Quantitative Rewriting is an innovative extension of traditional rewriting systems, in which rules are annotated with degrees drawn from a quantale. This framework provides a robust foundation for…

Logic in Computer Science · Computer Science 2025-07-29 Mauricio Ayala-Rincón , Thaynara Arielly de Lima , Georg Ehling , Temur Kutsia

The uniform one-dimensional fragment of first-order logic was introduced a few years ago as a generalization of the two-variable fragment to contexts involving relations of arity greater than two. Quantifiers in this logic are used in…

Logic in Computer Science · Computer Science 2025-03-19 Oskar Fiuk , Emanuel Kieronski

We present a new framework for assessing the power of measurement-based quantum computation (MBQC) on short-range entangled symmetric resource states, in spatial dimension one. It requires fewer assumptions than previously known. The…

Quantum Physics · Physics 2024-01-03 Robert Raussendorf , Wang Yang , Arnab Adhikary

This work is an enquiry into the circumstances under which entropy methods can give an answer to the questions of both quantum separability and classical correlations of a composite state. Several entropy functionals are employed to examine…

Quantum Physics · Physics 2009-11-07 A. K. Rajagopal , R. W. Rendell

The best empirical research in political science clearly defines substantive parameters of interest, presents a set of assumptions that guarantee its identification, and uses an appropriate estimator. We argue for the importance of…

Methodology · Statistics 2023-02-06 Nathan Canen , Kristopher Ramsay